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1. Astrocytes Drive Divergent Metabolic Gene Expression in Humans and Chimpanzees

   https://doi.org/10.1093/gbe/evad239  

   Zintel, Trisha M.; Pizzollo, Jason; Claypool, Christopher G.; Babbitt, Courtney C.; Satta, ed., Yoko (December 2023, Genome Biology and Evolution)

   Abstract The human brain utilizes ∼20% of all of the body's metabolic resources, while chimpanzee brains use <10%. Although previous work shows significant differences in metabolic gene expression between the brains of primates, we have yet to fully resolve the contribution of distinct brain cell types. To investigate cell type–specific interspecies differences in brain gene expression, we conducted RNA-seq on neural progenitor cells, neurons, and astrocytes generated from induced pluripotent stem cells from humans and chimpanzees. Interspecies differential expression analyses revealed that twice as many genes exhibit differential expression in astrocytes (12.2% of all genes expressed) than neurons (5.8%). Pathway enrichment analyses determined that astrocytes, rather than neurons, diverged in expression of glucose and lactate transmembrane transport, as well as pyruvate processing and oxidative phosphorylation. These findings suggest that astrocytes may have contributed significantly to the evolution of greater brain glucose metabolism with proximity to humans. 

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2. Comparative analysis of astrocytes in the prefrontal cortex of primates: Insights into the evolution of human brain energetics

   https://doi.org/10.1002/cne.25387  

   Munger, Emily_L; Edler, Melissa_K; Hopkins, William_D; Hof, Patrick_R; Sherwood, Chet_C; Raghanti, Mary_Ann (July 2022, Journal of Comparative Neurology)

   Abstract Astrocytes are the main homeostatic cell of the brain involved in many processes related to cognition, immune response, and energy expenditure. It has been suggested that the distribution of astrocytes is associated with brain size, and that they are specialized in humans. To evaluate these, we quantified astrocyte density, soma volume, and total glia density in layer I and white matter in Brodmann's area 9 of humans, chimpanzees, baboons, and macaques. We found that layer I astrocyte density, soma volume, and ratio of astrocytes to total glia cells were highest in humans and increased with brain size. Overall glia density in layer I and white matter were relatively invariant across brain sizes, potentially due to their important metabolic functions on a per volume basis. We also quantified two transporters involved in metabolism through the astrocyte‐neuron lactate shuttle, excitatory amino acid transporter 2 (EAAT2) and glucose transporter 1 (GLUT1). We expected these transporters would be increased in human brains due to their high rate of metabolic consumption and associated gene activity. While humans have higher EAAT2 cell density, GLUT1 vessel volume, and GLUT1 area fraction compared to baboons and chimpanzees, they did not differ from macaques. Therefore, EAAT2 and GLUT1 are not related to increased energetic demands of the human brain. Taken together, these data provide evidence that astrocytes play a unique role in both brain expansion and evolution among primates, with an emphasis on layer I astrocytes having a potentially significant role in human‐specific metabolic processing and cognition. 

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3. Chimpanzee fibroblasts exhibit greater adherence and migratory phenotypes than human fibroblasts

   https://doi.org/10.1101/838755  

   Zintel, T.M.; Ducey, D.; Babbitt, C.C. (November 2019, bioRxiv)

   null (Ed.)

   Background and objectives Previous work has identified that gene expression differences in cell adhesion pathways exist between humans and chimpanzees. Here, we used a comparative cell biology approach to assay interspecies differences in cell adhesion phenotypes in order to better understand the basic biological differences between species’ epithelial cells that may underly the organism-level differences we see in wound healing and cancer. Methodology We used skin fibroblast cell lines from humans and chimpanzees to assay cell adhesion and migration. We then utilized published RNA-Seq data from the same cell lines exposed to a cancer / wound-healing mimic to determine what gene expression changes may be corresponding to altered cellular adhesion dynamics between species. Results The functional adhesion and migration assays revealed that chimpanzee fibroblasts adhered sooner and remained adherent for significantly longer and move into a “wound” at faster rate than human fibroblasts. The gene expression data suggest that the enhanced adhesive properties of chimpanzee fibroblasts may be due to chimpanzee fibroblasts exhibiting significantly higher expression of cell and focal adhesion molecule genes than human cells, both during a wound healing assay and at rest. Conclusions and implications Chimpanzee fibroblasts exhibit stronger adhesion and greater cell migration than human fibroblasts. This may be due to divergent gene expression of focal adhesion and cell adhesion molecules, such as integrins, laminins, and cadherins, as well as ECM proteins like collagens. This is one of few studies demonstrating that these divergences in gene expression between closely related species can manifest in fundamental differences in cell biology. Our results provide better insight into species-specific cell biology phenotypes and how they may influence more complex traits, such as cancer metastasis and wound healing. 

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4. CellCover Defines Marker Gene Panels Capturing Developmental Progression in Neocortical Neural Stem Cell Identity

   https://doi.org/10.7554/eLife.107531.1  

   Ji, Lanlan; Wang, An; Sonthalia, Shreyash; Seo, Seungmae; Naiman, Daniel Q; Younes, Laurent; Colantuoni, Carlo; Geman, Donald (October 2025, eLife)

   Definition of cell classes across the tissues of living organisms is central in the analysis of growing atlases of single-cell RNA sequencing (scRNA-seq) data across biomedicine. Marker genes for cell classes are most often defined by differential expression (DE) methods that serially assess individual genes across landscapes of diverse cells. This serial approach has been extremely useful, but is limited because it ignores possible redundancy or complementarity across genes that can only be captured by analyzing multiple genes simultaneously. Interrogating binarized expression data, we aim to identify discriminating panels of genes that are specific to, not only enriched in, individual cell types. To efficiently explore the vast space of possible marker panels, leverage the large number of cells often sequenced, and overcome zero-inflation in scRNA-seq data, we propose viewing marker gene panel selection as a variation of the “minimal set-covering problem” in combinatorial optimization. Using scRNA-seq data from blood and brain tissue, we show that this new method, CellCover, performs as good or better than DE and other methods in defining cell-type discriminating gene panels, while reducing gene redundancy and capturing cell-class-specific signals that are distinct from those defined by DE methods. Transfer learning experiments across mouse, primate, and human data demonstrate that CellCover identifies markers of conserved cell classes in neocortical neurogenesis, as well as developmental progression in both progenitors and neurons. Exploring markers of human outer radial glia (oRG, or basal RG) across mammals, we show that transcriptomic elements of this key cell type in the expansion of the human cortex likely appeared in gliogenic precursors of the rodent before the full program emerged in neurogenic cells of the primate lineage. We have assembled the public datasets we use in this report within the NeMO Analytics multi-omic data exploration environment [1], where the expression of individual genes (NeMO: Individual genes in cortex and NeMO: Individual genes in blood) and marker gene panels (NeMO: Telley 3 CellCover Panels, NeMO: Telley 12 CellCover Panels, NeMO: Sorted Brain Cell CellCover Panels, and NeMO: Blood 34 CellCover Panels) can be freely explored without coding expertise. CellCover is available in CellCover R and CellCover Python. 

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5. Multispecies characterization of immature neurons in the mammalian amygdala reveals their expansion in primates

   https://doi.org/10.1371/journal.pbio.3003322  

   Ghibaudi, Marco; La_Rosa, Chiara; Telitsyn, Nikita; Graїc, Jean-Marie; Faulkes, Chris G; Sherwood, Chet C; Bonfanti, Luca (August 2025, PLOS Biology)

   Fudge, Julie (Ed.)

   Structural changes involving new neurons can occur through stem cell-driven neurogenesis, and through incorporation of late-maturing “immature” neurons into networks, namely undifferentiated neuronal precursors frozen in a state of arrested maturation. The latter have been found in the cerebral cortex and are particularly abundant in large-brained mammals, covarying with the size of the brain and cortex. Similar cells have been described in the amygdala of some species, although their features and interspecies variation remain poorly understood. Here, their occurrence, number, morphology, molecular expression, age-related changes, and anatomical distribution in amygdala subdivisions were systematically analyzed in eight diverse mammalian species (including mouse, naked mole rat, rabbit, marmoset, cat, sheep, horse, and chimpanzee) widely differing in neuroanatomy, brain size, life span, and socioecology. We identify converging evidence that these amygdala cells are immature neurons and show marked phylogenetic variation, with a significantly greater prevalence in primates. The immature cells are largely located within the amygdala’s basolateral complex, a region that has expanded in primate brain evolution in conjunction with cortical projections. In addition, amygdala immature neurons also appear to stabilize in number through adulthood and old age, unlike other forms of plasticity that undergo marked age-related reduction. These results support the emerging view that large brains performing complex socio-cognitive functions rely on wide reservoirs of immature neurons. 

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